Empowering data excellence for agility and scalability

A leading media conglomerate spearheaded a comprehensive data transformation with Systech’s data migration expertise, for unparalleled performance, cost efficiency, and data accessibility.

BUSINESS NEED 

A prominent media industry leader faced significant challenges in data management due to an aging infrastructure. With data siloed across various departments, trust in data quality was low, and collaboration between teams was hampered. The organization needed a modern, scalable solution to unify its data architecture and enhance overall operational efficiency. 

SYSTECH’S DELIVERY 

Systech, leveraging its extensive expertise in data engineering and cloud solutions, facilitated a comprehensive migration from AWS Redshift to Snowflake, aimed at creating a unified, efficient, and scalable data architecture, thereby democratizing data access across the organization and improving decision-making capabilities. 

OVERVIEW 

The client’s legacy data infrastructure lacked the scalability needed to support growing data volumes and the flexibility required for modern data processing. To address these issues, Systech implemented a full-scale transformation of the data architecture, migrating to Snowflake—a highly scalable, cloud-native data warehouse with a serverless design. This also enhanced data governance and cataloging, as well as decommissioned expensive BI tools. 

THE CHALLENGE 

The client faced significant challenges in their data management, with departmental silos creating trust issues and inefficiencies in data sharing and usage. The existing architecture was complex, involving multiple tools and processes that required seamless integration during migration. Additionally, AWS Redshift’s limitations in handling semi-structured data and scaling efficiently were impacting overall performance. The high licensing costs for tools like Looker further underscored the need for a more cost-effective solution. 

THE DETAILED SOLUTION PROCESS 

A thorough assessment of the existing data infrastructure, including mapping out all data sources, identifying dependencies, and understanding the client’s business goals led to a comprehensive migration strategy, designed to minimize risk and ensure a smooth transition. 

A migration pipeline using Python, Databricks, and DBT handled data transformation processes. These tools were integrated into the existing pipelines to ensure that data was consistently formatted and ready for migration. 

Snowflake configuration and implementation for a serverless architecture, allowing for dynamic scaling and efficient handling of both structured and semi-structured data. This included setting up virtual warehouses with different compute capabilities, enabling the client to tailor processing power to specific workloads. 

A dual system approach with both AWS Redshift and Snowflake being operational, ensured that the client’s business operations were not disrupted during the transition. Data was continuously synchronized between the two systems to maintain consistency. 

To reduce costs and improve efficiency, Looker was decommissioned and replaced with custom-built solutions leveraging Snowflake’s capabilities. This eliminated licensing costs and streamlined the data querying process. The phased migration, robust monitoring and iterative testing protocols allowed for continuous improvement and adaptation to any challenges that arose. 

THE IMPACT 

A dramatic increase in query performance. Snowflake’s ability to scale compute resources dynamically allowed for faster data processing and quicker insights. The client reported a noticeable improvement in operational efficiency and data-driven decision-making.

Cost efficiency. By decommissioning Looker and optimizing the data architecture, the client achieved substantial cost savings. Snowflake’s pay-per-use model and serverless architecture further reduced operational expenses, making the solution both cost-effective and scalable. 

Data silos were broken down. With this implementation, trust in data quality was restored. Teams across the organization could now access and collaborate on data with confidence, leading to better alignment and more informed business decisions. 

The new data architecture not only met the client’s current needs but also positioned them for future growth. The flexibility and scalability of Snowflake, combined with the robust data governance ensured that the client was well-equipped to handle future data challenges and opportunities. 

THE ADDED VALUE 

With the new Snowflake architecture, the client gained scalable flexibility, optimizing resources and reducing costs. The robust data cataloging and governance leveraged data quality and accessibility across the organization. Systech’s strategic dual system management ensured a smooth, disruption-free migration, positioning the client for future growth with enhanced performance and efficiency. This success highlights Systech’s ability to drive operational excellence and long-term value through strategic data transformation. 

Elevate your data strategy with Systech’s tailored data migration services. https://systechusa.com/analytics/  

Get in touch with us to explore how we can drive your data success. https://systechusa.com/industries/media-entertainment/  

Related Resources:

ADVANCED ANALYTICS, AI & MACHINE LEARNING

Automate, enrich and innovate with Systech’s Data Science, ML and AI service offerings.